Teams unknowingly run AWS like it's 2018 — self-managed K8s clusters, EC2 for everything, legacy networking — wasting 30-80% on ops and cost when newer managed services exist.
Connect to an AWS account via read-only IAM role. The tool maps all resources, compares against current AWS best practices and service capabilities, and generates a prioritized report: 'Replace this self-managed K8s cluster with ECS Fargate to save ~$X/month and eliminate Y ops hours.' Continuously re-scans as AWS evolves.
Real pain but often invisible — teams don't know they're wasting money on outdated patterns because everything 'works.' The pain is diffuse (slow ops velocity + excess cost) rather than acute (system is down). Budget pressure and layoffs in 2024-2026 are making engineering leaders more cost-conscious, which helps. But this is a 'vitamin not painkiller' risk — teams can ignore this for years.
TAM is massive. ~1M+ companies use AWS, ~100K+ have meaningful spend ($10K+/mo). Mid-size teams (your target) number in tens of thousands. At $299-999/mo, even capturing 1,000 customers = $3.6-12M ARR. The adjacent cloud cost optimization market is $5B+ and growing. Architectural modernization advice specifically is underserved by tooling.
Mixed signals. Engineering teams are used to free AWS-native tools (Trusted Advisor, Cost Explorer). $299-999/mo is reasonable if you can show 10x ROI (save $3K-10K/mo), but proving that before they buy is the challenge. Enterprises will pay, but mid-size teams have tighter budgets and more 'we can do this ourselves' mentality. The free scan needs to show jaw-dropping savings to convert. Consulting firms charge $50K+ for this analysis, so there's willingness — but from tool? Less proven.
Read-only IAM scan and resource mapping is straightforward — AWS APIs are well-documented. The HARD part is the recommendation engine: mapping thousands of resource configurations to modernization advice requires deep, constantly-updated AWS expertise. You need to know that 'RDS MySQL 5.7 on m5.xlarge with these access patterns should be Aurora Serverless v2' — that's domain expertise encoded as rules/heuristics. An MVP with 10-15 high-value rules (EC2→Fargate, self-managed K8s→EKS/ECS, NAT Gateway optimization, GP2→GP3, etc.) is doable in 6-8 weeks for a strong AWS engineer. But the moat IS the rule quality, and keeping it current is ongoing work.
This is the strongest signal. Every existing tool optimizes WITHIN your current architecture (rightsizing, reserved instances, spot). NOBODY automates the question 'should you even be using this service/pattern at all?' AWS Well-Architected is a manual questionnaire. Consulting firms do this but charge $50-200K. There's a clear gap for an automated, opinionated modernization advisor. The closest thing is a senior AWS architect doing a manual review — you're productizing that.
Strong recurring model. AWS releases 60+ new services/year, so recommendations need constant updating. Infrastructure drifts as teams add resources. Continuous monitoring catches new waste. Slack alerts and migration tracking are inherently ongoing. The 'your infrastructure is a living thing' narrative supports subscription well. Risk: if recommendations are too good, customers modernize and churn — but AWS sprawl means new waste always appears.
- +Clear gap in market: nobody automates architectural modernization advice — all competitors optimize within existing patterns, not across them
- +Massive TAM with strong tailwinds: cloud cost pressure + AWS service proliferation + aging cloud infrastructure
- +High-value free scan is a powerful acquisition channel — 'connect your AWS account, see how much you're wasting in 5 minutes' is a compelling hook
- +Defensible moat via depth of recommendation rules — hard for competitors to bolt this on as a feature
- +Natural expansion path: multi-account, multi-cloud, compliance, team workflows
- !AWS could build this natively — they've been investing in migration tooling and Trusted Advisor. A single AWS re:Invent announcement could commoditize your core value prop.
- !Rule quality is everything and is expensive to maintain — bad recommendations destroy trust instantly. One 'migrate to Fargate' suggestion that doesn't account for GPU workloads or specific networking needs = lost customer.
- !Mid-size teams may prefer a one-time audit over continuous subscription — 'we ran the scan, got the report, now we'll fix things over 6 months' creates churn risk.
- !Security-conscious teams will hesitate to grant read-only IAM access to a startup — enterprise sales motion may be needed for larger accounts, which is slower and harder as a solo founder.
- !Quantifying savings accurately is critical but extremely hard — if you say 'save $5K/mo' and they save $500, credibility is gone.
AWS-native tools that review workloads against best practices across cost, performance, security, and reliability pillars. Trusted Advisor flags underutilized resources; Well-Architected Tool runs structured reviews.
Cloud cost observability platform. Shows granular cost breakdowns, rightsizing recommendations, savings plans optimization, and cost anomaly detection across AWS, GCP, Azure.
Infracost shows cost estimates for Terraform changes pre-deployment. Cloud Posse provides reference architectures. env0 manages IaC workflows with cost guardrails.
Enterprise cloud cost management platforms. CloudHealth
Automated cloud infrastructure optimization. Spot.io manages spot instances, rightsizing, and scaling. Cast.ai specifically optimizes Kubernetes costs by automating bin-packing and instance selection.
Single AWS account scanner via read-only IAM role. Start with 10-15 high-impact, high-confidence rules: (1) EC2 instances that should be Fargate/Lambda, (2) self-managed K8s → EKS/ECS Fargate, (3) GP2 → GP3 EBS volumes, (4) old-gen instance types, (5) NAT Gateway cost optimization, (6) RDS → Aurora Serverless v2 candidates, (7) ElastiCache → DynamoDB DAX candidates, (8) Classic ELB → ALB migration, (9) unused/underutilized resources, (10) reserved instance vs savings plan optimization. Output: a beautiful, shareable PDF/web report with estimated savings per recommendation and difficulty rating (easy/medium/hard). No continuous monitoring in v1 — just one-time scans with re-scan capability.
Free one-time scan (single account, summary report with top 5 findings) → $299/mo Pro (full report, all rules, re-scan weekly, Slack alerts, up to 3 accounts) → $999/mo Team (unlimited accounts, migration playbooks with step-by-step Terraform/CDK code, team dashboard, priority rule requests, Jira integration) → Enterprise custom pricing (SSO, compliance reports, dedicated rule development, SLA). Consider also a one-time audit report at $499-1999 for teams that won't subscribe.
8-12 weeks to first dollar. Weeks 1-4: build scanner + 10 core rules + report generation. Weeks 5-6: landing page, free scan flow, Stripe integration. Weeks 7-8: beta with 10-20 teams from AWS communities/Reddit/Twitter. Weeks 9-12: iterate on rule quality based on feedback, convert free users to paid. First paying customers likely from the free scan showing $5K+/mo in potential savings — the report sells itself.
- “treating AWS like it's 2018 — spinning up EC2 instances for everything”
- “a lot of companies are still running self-managed Kubernetes clusters when ECS Fargate or even Lambda would cut their ops burden by 80%”
- “half our best practices are outdated in a year”
- “outdated blog posts still spread old assumptions”